All these features come with a single box, you just need to specify which modules you want to use using a configuration file (config.properties) and Rakam will do the rest for you.We also provide cloud deployment tools for scaling your Rakam cluster easily.

Deployment

If your event data-set can fit in a single server, we recommend using Postgresql backend. Rakam will collect all your events in row-oriented format in a Postgresql node. All the features provided by Rakam are supported in Postgresql deployment type.

However Rakam is designed to be highly scalable in order to provide a solution for high work-loads. You can configure Rakam to send events to a distributed commit-log such as Apache Kafka or Amazon Kinesis in serialized Apache Avro format and process data in PrestoDB workers and store them in a distributed filesystem in a columnar format.

Heroku

You can deploy Rakam to Heroku using Heroku button, it uses Heroku Postgresql add-on for your app and uses Postgresql deployment type.

Digitalocean

Digitalocean installer uses Docker under the hood. It will install Docker on your droplet and run docker image of Postgresql and link it with your Rakam container. The API the image exposes is 9999, you may visit your Rakam API address from YOUR_DROPLET_IP:80. The default lock key is mylockKey.

Docker

Run the following command to start a Postgresql server in docker container and Rakam API in your local environment.

You can set config variables for Rakam instance using environment variables. All properties in config.properties file can be set via environment variable RAKAM_CONFIG_property_name_dots_replaced_by_underscore.For example, if you want to set store.adapter=postgresql you need to set environment variable RAKAM_CONFIG_STORE_ADAPTER=postgresql.

Dockerfile will generate config.properties file from environment variables in docker container that start with RAKAM_CONFIG prefix.

In order to set environment variables for container, you may use -e flag for for docker run but we advice you to set all environment variables in a file and use --env-file flag when starting your container.

Then you can share same file among the Rakam containers. If Dockerfile can't find any environment variable starts with RAKAM_CONFIG, it tries to connect Postgresql instance created with docker-compose.

AWS (Cloudformation)

Cloudformation templates create a Opsworks stack in your AWS account for Rakam. You can easily monitor, scale and manage your Rakam cluster with these Cloudformation templates.

Cloudformation is the recommended way to deploy Rakam in production because AWS automatically handles most of the complexity like fail over and load-balancing.

Custom

Download latest version from Bintray, ([VERSION]/rakam-[VERSION]-.bundle.tar.gz) extract package, modify etc/config.properties(sample for Postgresql deployment type) file and run bin/launcher start.The launcher script can take the following arguments: start|restart|stop|status|run.bin/launcher run will start Rakam in foreground.

Building Rakam

You can try the master branch by pulling the source code from Github and building Rakam using Maven:

Running Rakam in your IDE

Since we already use Maven, you can import Rakam to your IDE using the root pom.xml file. We recommend using Intellij IDEA since the core team uses it when developing Rakam. Here is a sample configuration for executing Rakam in your IDE:

Managed

We're also working for managed Rakam cluster, we will deploy Rakam to our AWS accounts and manage it for you so that you don't need to worry about scaling, managing and software updates. We will do it for you.Please shoot us an email to emre@rakam.io if you want to test our managed Rakam service.

Web application

This repository contains Rakam API server that allows you to interact with Rakam using a REST interface. If you already have a frontend and developed a custom analytics service based on Rakam, it's all you need.

However, we also developed Rakam Web Application that allows you to analyze your user and event data-set but performing SQL queries, visualising your data in various charts, creating (real-time) dashboards and custom reports. You can turn Rakam into a analytics web service similar to Mixpanel, Kissmetrics and Localytics using the web application. Otherwise, Rakam server is similar to Keen.io with SQL as query language and some extra features.

Another nice property of Rakam web application is being BI (Business Intelligence) tool. If you can disable collect APIs and connect Rakam to your SQL database with JDBC adapter and use Rakam application to query your data in your database. Rakam Web Application has various charting formats, supports parameterized SQL queries, custom pages that allows you to design pages with internal components.

Contribution

Currently I'm actively working on Rakam. If you want to contribute the project or suggest an idea feel free to fork it or create a ticket for your suggestions. I promise to respond you ASAP.The purpose of Rakam is being generic data analysis tool which can be a solution for many use cases. Rakam still needs too much work and will be evolved based on people's needs so your thoughts are important.

Acknowledgment

We use YourKit Java Profiler in order to monitor the JVM instances for identifing the bugs and potential bottlenecks. Kudos to YourKit for supporting Rakam with your full-featured Java Profile!